Abstract
The relevance of improving the functioning of transport and logistics processes in Russia at the present stage of its development is shown. It is known that due to numerous uncertainties of infrastructural and technological interaction of cargo carriers, such as bad weather conditions, technical and technological problems, as well as temporary ones (for example, adjusting the plan for the wagons and ships supply), it is difficult to ensure adaptive and flexible strategic planning and management in the port transport system. Under the current conditions, the further development of port transport and technological systems is advisable not only due to the strengthening of the transport infrastructure, but also due to the introducing and improving information and logistics systems in limiting areas, advanced methods of managing the transportation process, improving technologies, increasing efficiency of interaction between transport participants and intellectualizing transport and logistics chains (TLC) management. The use of hybrid neuro-fuzzy modeling of transport and logistics processes, which integrates the natural intelligence of a specialist-expert and the intelligence of a machine (artificial intelligence based on the use of neural networks), is substantiated. The main logical and linguistic “statements” of economic agents (EA) interaction are described. An iterative mechanism for the interaction of economic entities of transport and logistics chains has been developed based on the adapted Ashby’s homeostat principle. The developed procedure for managing transport and logistics chains and their links ensures automatic adaptation of the transport process to the specified performance indicators, the capabilities of TLC links and external influences.
The reported study was funded by RFBR, Sirius University of Science and Technology, JSC Russian Railways and Educational Fund «Talent and success», project number 20-38-51014.
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Bakalov, M.V., Lyabakh, N.N., Vereskun, V.D., Zadorozhniy, V.M. (2023). Intelligent Support for the Interaction of Transport Process Participants Using Fuzzy Modeling. In: Kovalev, S., Sukhanov, A., Akperov, I., Ozdemir, S. (eds) Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). IITI 2022. Lecture Notes in Networks and Systems, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-031-19620-1_38
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